thought starter 2: remote sensing: role, opportunities and challenges · frédéric achard, joint...

Frédéric Achard, Joint Research Centre, European Commission

Thought starter 2: Remote sensing: role, opportunities and

challenges

CPF Organization-Led Initiative (OLI)

Rome, November 28-30, 2016

Content

Availability of Remote Sensing data for monitoring forest cover

Global or National Surveys using Remote sensing data:

– Global Forest Watch – Remote Sensing Survey of FAO FRA-2010– Global Forest Survey (GFS) of FAO– Brazilian remote sensing survey

Global Biomass Mapping initiatives

Characteristics of Landsat-8 OLI and Sentinel-2 sensors

Nation Satellite Resolution& coverage

Cost for data Feature

USA Landsat-8OLI

15 m – 30 m16 days

All data archivedat USGS are free

Data are systematicallyacquired since June 2013

EU Sentinel-2 10 m- 20 m5 – 10 days

All data archivedat ESA are free

Data are systematicallyacquired from July 2016

Global availability of Landsat and Sentinel-2 data

Two main sources of free global mid-resolution remote sensing imagery:

- from NASA (Landsat satellites) for data acquired since early 1980s - from ESA (Sentinels satellites through Copernicus programme) for data

acquired since mid-2010’s

Multispectral LANDSAT 8 image30 m pixel resolution

22 Jan 2015

525 November 2016Sentinel-2 Image, Democratic Republic of the Congo, 50km North of Yangambi

Image size: ~ 15 km × 10 km ; date : 22 September 2015

Detection of Logging roads in DR Congo

Global or National Surveys using Remote sensing data for forestry statistics

Global Forest Watch

Remote Sensing Survey of FAO FRA-2010

Global Forest Survey (GFS) of FAO

Brazilian remote sensing survey

Global Forest Cover Change Mapping: Global Forest Watch dataset (WRI / Google / Univ. Maryland)

Global Remote Sensing Survey of FRA-2010

Gross forest and OWL loss during period 2000-2010

COLLECT EARTHAN OPEN SOURCE TOOL FOR AUGMENTED VISUALINTERPRETATION

COLLECT EARTHAN OPEN SOURCE TOOL FOR AUGMENTED VISUALINTERPRETATION

Example of Systematic Sample at national level:

Landscape Units of the Brazilian National Forest Inventory

Location of the landscape Sample Units

for the state of Parana

• Sampling intensity: every 40km x 40km

• Size of SU: 10km x 10km

• Each SU is covered by Satellite imagery (RapidEye at 5 m res.)

• Data collection=imagery interpretation

Global Biomass Mapping: Existing datasets

Map Coverage Resol. Year RS input data Organization

Saatchi et al. (2011) Tropics 1 Km c. 2000‐2001 MODIS, GLAS NASA

Baccini et al. (2012) Tropics 500 m 2006‐2007 MODIS, GLAS WHRC

Avitabile et al. (2016) Tropics 1 Km 2000’s Saatchi & Baccini maps EU GEOCARBON

Thurner et al. (2014) Boreal 1 Km 2010 Envisat ASAR ESA BIOMASAR

Thurner et al. (2014)

Map Coverage Resol. Year RS input data Organization

Baccini et al. (2016) Tropics 30 m 2000 Landsat, GLAS WHRC ‐ GFW

Saatchi et al. (in review) Global 100 m 2010 Landsat, GLAS, Wood density NASA

Santoro et al. (in prep.) Global ̴100 m 2010 Landsat, GLAS, ALOS ESA ‐ GlobBiomass

Global Biomass Mapping: New/upcoming datasets

Thanks for your attention